High-Performance Dual-Arm Task and Motion Planning for Tabletop Rearrangement

• URL: http://arxiv.org/abs/2512.08206v2
• Date: Sat, 28 Feb 2026 03:49:10 GMT
• Title: High-Performance Dual-Arm Task and Motion Planning for Tabletop Rearrangement
• Abstract summary: Two robot arms equipped with 2-finger grippers must work together in close proximity to rearrange objects whose start and goal configurations are strongly entangled.<n>We propose Synchronous Dual-Arm Rearrangement Planner (SDAR), a task and motion planning framework for tabletop rearrangement.<n>We show that SDAR delivers a 100% success rate in solving complex, non-monotone, long-horizon tabletop rearrangement tasks.
• Score: 17.516999633167522
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose Synchronous Dual-Arm Rearrangement Planner (SDAR), a task and motion planning (TAMP) framework for tabletop rearrangement, where two robot arms equipped with 2-finger grippers must work together in close proximity to rearrange objects whose start and goal configurations are strongly entangled. To tackle such challenges, SDAR tightly knit together its dependency-driven task planner (SDAR-T) and synchronous dual-arm motion planner (SDAR-M), to intelligently sift through a large number of possible task and motion plans. Specifically, SDAR-T applies a simple yet effective strategy to decompose the global object dependency graph induced by the rearrangement task, to produce more optimal dual-arm task plans than solutions derived from optimal task plans for a single arm. Leveraging state-of-the-art GPU SIMD-based motion planning tools, SDAR-M employs a layered motion planning strategy to sift through many task plans for the best synchronous dual-arm motion plan while ensuring high levels of success rate. Comprehensive evaluation demonstrates that SDAR delivers a 100% success rate in solving complex, non-monotone, long-horizon tabletop rearrangement tasks with solution quality far exceeding the previous state-of-the-art. Experiments on two UR-5e arms further confirm SDAR directly and reliably transfers to robot hardware. Source code and supplementary materials are available at https://github.com/arc-l/dual-arm.

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